Skip to main content

Python/C++ library for distribution power system analysis

Project description

PyPI version Anaconda-Server Badge License: MIT Build and Test C++ and Python Check Code Quality Clang Tidy REUSE Compliance Check docs Downloads Downloads

Quality Gate Status Coverage Maintainability Rating Reliability Rating Security Rating Vulnerabilities

DOI

Power Grid Model

power-grid-model is a library for steady-state distribution power system analysis distributed for Python and C. The core of the library is written in C++. Currently, it supports the following calculations:

  • Power Flow
  • State Estimation
  • Short Circuit

See the power-grid-model documentation for more information. For various conversions to the power-grid-model, refer to the power-grid-model-io repository.

Want to be updated on the latest news and releases? Subscribe to the Power Grid Model mailing list by sending an (empty) email to: powergridmodel+subscribe@lists.lfenergy.org

Installation

Install from PyPI

You can directly install the package from PyPI.

pip install power-grid-model

Install from Conda

If you are using conda, you can directly install the package from conda-forge channel.

conda install -c conda-forge power-grid-model

Build and install from Source

To install the library from source, refer to the Build Guide.

Examples

Please refer to Examples for more detailed examples for power flow and state estimation. Notebooks for validating the input data and exporting input/output data are also included.

License

This project is licensed under the Mozilla Public License, version 2.0 - see LICENSE for details.

Licenses third-party libraries

This project includes third-party libraries, which are licensed under their own respective Open-Source licenses. SPDX-License-Identifier headers are used to show which license is applicable. The concerning license files can be found in the LICENSES directory.

Contributing

Please read CODE_OF_CONDUCT, CONTRIBUTING, PROJECT GOVERNANCE and RELEASE for details on the process for submitting pull requests to us.

Visit Contribute for a list of good first issues in this repo.

Citations

If you are using Power Grid Model in your research work, please consider citing our library using the following references.

DOI

@software{Xiang_PowerGridModel_power-grid-model,
  author = {Xiang, Yu and Salemink, Peter and Bharambe, Nitish and Govers, Martinus and van den Bogaard, Jonas and Stoeller, Bram and Wang, Zhen and Guo, Jerry and Jagutis, Laurynas and Wang, Chenguang and van Raalte, Marc and {Contributors to the LF Energy project Power Grid Model}},
  doi = {10.5281/zenodo.8054429},
  license = {MPL-2.0},
  title = {{PowerGridModel/power-grid-model}},
  url = {https://github.com/PowerGridModel/power-grid-model}
}
@inproceedings{Xiang2023,
  author = {Xiang, Yu and Salemink, Peter and Stoeller, Bram and Bharambe, Nitish and van Westering, Werner},
  booktitle = {CIRED 2023 - The 27th International Conference and Exhibition on Electricity Distribution},
  title = {Power grid model: A high-performance distribution grid calculation library},
  year = {2023},
  volume={2023},
  number = {},
  pages={1-5}
}

Contact

Please read SUPPORT for how to connect and get into contact with the Power Gird Model project.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

power-grid-model-1.6.53.tar.gz (732.7 kB view details)

Uploaded Source

Built Distributions

power_grid_model-1.6.53-py3-none-win_amd64.whl (504.2 kB view details)

Uploaded Python 3 Windows x86-64

power_grid_model-1.6.53-py3-none-musllinux_1_2_x86_64.whl (1.6 MB view details)

Uploaded Python 3 musllinux: musl 1.2+ x86-64

power_grid_model-1.6.53-py3-none-manylinux_2_24_x86_64.whl (737.8 kB view details)

Uploaded Python 3 manylinux: glibc 2.24+ x86-64

power_grid_model-1.6.53-py3-none-manylinux_2_24_aarch64.whl (683.8 kB view details)

Uploaded Python 3 manylinux: glibc 2.24+ ARM64

power_grid_model-1.6.53-py3-none-macosx_11_0_arm64.whl (552.5 kB view details)

Uploaded Python 3 macOS 11.0+ ARM64

power_grid_model-1.6.53-py3-none-macosx_10_9_x86_64.whl (595.3 kB view details)

Uploaded Python 3 macOS 10.9+ x86-64

File details

Details for the file power-grid-model-1.6.53.tar.gz.

File metadata

  • Download URL: power-grid-model-1.6.53.tar.gz
  • Upload date:
  • Size: 732.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.13

File hashes

Hashes for power-grid-model-1.6.53.tar.gz
Algorithm Hash digest
SHA256 ac6c922ae1fffe7878334c502d9c95e34c803f1fc87b7ea57f16d14d37a79da8
MD5 1728114c3f574ea78258a346a508f8d2
BLAKE2b-256 6b1c82864544ed3c053d7f30519f19026b62f537d60ee89a51c007098bf76f91

See more details on using hashes here.

File details

Details for the file power_grid_model-1.6.53-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.6.53-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 7e3218d7f51fe69915c92121b1feb80c30328d15272a6e1f926bba25ad4cb591
MD5 d1c16df19fe3c63332d119453e3cdde2
BLAKE2b-256 546d8ea307af265e062b067c447061a82e78737cfc2f9fa606e5c7f9e17eb835

See more details on using hashes here.

File details

Details for the file power_grid_model-1.6.53-py3-none-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.6.53-py3-none-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 6050494289ccb094fcc4f7a74ce915fe60a658f86ff05481498b26be09b03044
MD5 ac8a320b365affd6d8062a7a732559c4
BLAKE2b-256 28d8ea1133bb6513f913ca2ec5477d8a6056edeca491da6625cc997228d78e69

See more details on using hashes here.

File details

Details for the file power_grid_model-1.6.53-py3-none-manylinux_2_24_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.6.53-py3-none-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 b1a06441837c13c3c5bc938912e9d74df389afd93e1e3c80d2602d9d25362da2
MD5 a01342c8b309549ce92ee3305c596dab
BLAKE2b-256 46c323de9ef944f72ac5a92d2170aa34c5cc8f76966fe889fe41876fe926e7e0

See more details on using hashes here.

File details

Details for the file power_grid_model-1.6.53-py3-none-manylinux_2_24_aarch64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.6.53-py3-none-manylinux_2_24_aarch64.whl
Algorithm Hash digest
SHA256 76f126c163bbbdf82a6dd2fcb1e6f7c3f5c6bca1c46c7897a4344f2e21874945
MD5 d1033e850bbbe09f96a0420fb89a3149
BLAKE2b-256 7aef2064d9f02f4b79feaf62307886126a99ba3e237ba8d2e49f5cf94a30cdd5

See more details on using hashes here.

File details

Details for the file power_grid_model-1.6.53-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.6.53-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b036e8e5f9e9e9893395f7b9992e42e142c0f5950d574a954842510dcacde3ee
MD5 7d5bab189cff878b9698ce45801c3e6b
BLAKE2b-256 c388b8217ebffbe5f5b446233182ce82ef9eb4a0404bd54516b4f0dfd072295f

See more details on using hashes here.

File details

Details for the file power_grid_model-1.6.53-py3-none-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.6.53-py3-none-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 295a0e9de42cf0dd68359022b45d9b573e1d39b41b92306d11caec9152b8de9f
MD5 d2c5d5f77f940de27a71ec917cc25736
BLAKE2b-256 3b848588dcdff4f784bf3b4194a9643b97d7ceff3470e42504e3a971fd7a8fa9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page